mne.preprocessing.compute_current_source_density¶

mne.preprocessing.compute_current_source_density(inst, sphere='auto', lambda2=1e-05, stiffness=4, n_legendre_terms=50, copy=True)[source]¶

Get the current source density (CSD) transformation.

Transformation based on spherical spline surface Laplacian 1 2 3 4.

Parameters

instinstance of Raw, Epochs or Evoked: The data to be transformed.
spherearray_like, shape (4,) | str: The sphere, head-model of the form (x, y, z, r) where x, y, z is the center of the sphere and r is the radius in meters. Can also be “auto” to use a digitization-based fit.
lambda2float: Regularization parameter, produces smoothness. Defaults to 1e-5.
stiffnessfloat: Stiffness of the spline.
n_legendre_termsint: Number of Legendre terms to evaluate.
copybool: Whether to overwrite instance data or create a copy.

Returns

inst_csdinstance of Raw, Epochs or Evoked: The transformed data. Output type will match input type.

Notes

This function applies an average reference to the data if copy is False. Do not transform CSD data to source space.

New in version 0.20.

References

1: F. Perrin, O. Bertrand, and J. Pernier. Scalp Current Density Mapping: Value and Estimation from Potential Data. IEEE Transactions on Biomedical Engineering, BME-34(4):283–288, April 1987. doi:10.1109/TBME.1987.326089.
2: François M. Perrin, Jacques Pernier, Olivier M. Bertrand, and Jean Franćois Echallier. Spherical splines for scalp potential and current density mapping. Electroencephalography and Clinical Neurophysiology, 72(2):184–187, 1989. doi:10.1016/0013-4694(89)90180-6.
3: Mike X. Cohen. Analyzing Neural Time Series Data: Theory and Practice. MIT Press, 2014.
4: Jürgen Kayser and Craig E. Tenke. On the benefits of using surface Laplacian (Current Source Density) methodology in electrophysiology. International journal of psychophysiology : official journal of the International Organization of Psychophysiology, 97(3):171–173, September 2015. doi:10.1016/j.ijpsycho.2015.06.001.